Marcos García

Also published as: Marcos Garcia


2022

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Proceedings of the 18th Workshop on Multiword Expressions @LREC2022
Archna Bhatia | Paul Cook | Shiva Taslimipoor | Marcos Garcia | Carlos Ramisch
Proceedings of the 18th Workshop on Multiword Expressions @LREC2022

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SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding
Harish Tayyar Madabushi | Edward Gow-Smith | Marcos Garcia | Carolina Scarton | Marco Idiart | Aline Villavicencio
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)

This paper presents the shared task on Multilingual Idiomaticity Detection and Sentence Embedding, which consists of two subtasks: (a) a binary classification task aimed at identifying whether a sentence contains an idiomatic expression, and (b) a task based on semantic text similarity which requires the model to adequately represent potentially idiomatic expressions in context. Each subtask includes different settings regarding the amount of training data. Besides the task description, this paper introduces the datasets in English, Portuguese, and Galician and their annotation procedure, the evaluation metrics, and a summary of the participant systems and their results. The task had close to 100 registered participants organised into twenty five teams making over 650 and 150 submissions in the practice and evaluation phases respectively.

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The Nós Project: Opening routes for the Galician language in the field of language technologies
Iria de-Dios-Flores | Carmen Magariños | Adina Ioana Vladu | John E. Ortega | José Ramom Pichel | Marcos García | Pablo Gamallo | Elisa Fernández Rei | Alberto Bugarín-Diz | Manuel González González | Senén Barro | Xosé Luis Regueira
Proceedings of the Workshop Towards Digital Language Equality within the 13th Language Resources and Evaluation Conference

The development of language technologies (LTs) such as machine translation, text analytics, and dialogue systems is essential in the current digital society, culture and economy. These LTs, widely supported in languages in high demand worldwide, such as English, are also necessary for smaller and less economically powerful languages, as they are a driving force in the democratization of the communities that use them due to their great social and cultural impact. As an example, dialogue systems allow us to communicate with machines in our own language; machine translation increases access to contents in different languages, thus facilitating intercultural relations; and text-to-speech and speech-to-text systems broaden different categories of users’ access to technology. In the case of Galician (co-official language, together with Spanish, in the autonomous region of Galicia, located in northwestern Spain), incorporating the language into state-of-the-art AI applications can not only significantly favor its prestige (a decisive factor in language normalization), but also guarantee citizens’ language rights, reduce social inequality, and narrow the digital divide. This is the main motivation behind the Nós Project (Proxecto Nós), which aims to have a significant contribution to the development of LTs in Galician (currently considered a low-resource language) by providing openly licensed resources, tools, and demonstrators in the area of intelligent technologies.

2021

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Assessing the Representations of Idiomaticity in Vector Models with a Noun Compound Dataset Labeled at Type and Token Levels
Marcos Garcia | Tiago Kramer Vieira | Carolina Scarton | Marco Idiart | Aline Villavicencio
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Accurate assessment of the ability of embedding models to capture idiomaticity may require evaluation at token rather than type level, to account for degrees of idiomaticity and possible ambiguity between literal and idiomatic usages. However, most existing resources with annotation of idiomaticity include ratings only at type level. This paper presents the Noun Compound Type and Token Idiomaticity (NCTTI) dataset, with human annotations for 280 noun compounds in English and 180 in Portuguese at both type and token level. We compiled 8,725 and 5,091 token level annotations for English and Portuguese, respectively, which are strongly correlated with the corresponding scores obtained at type level. The NCTTI dataset is used to explore how vector space models reflect the variability of idiomaticity across sentences. Several experiments using state-of-the-art contextualised models suggest that their representations are not capturing the noun compounds idiomaticity as human annotators. This new multilingual resource also contains suggestions for paraphrases of the noun compounds both at type and token levels, with uses for lexical substitution or disambiguation in context.

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Exploring the Representation of Word Meanings in Context: A Case Study on Homonymy and Synonymy
Marcos Garcia
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

This paper presents a multilingual study of word meaning representations in context. We assess the ability of both static and contextualized models to adequately represent different lexical-semantic relations, such as homonymy and synonymy. To do so, we created a new multilingual dataset that allows us to perform a controlled evaluation of several factors such as the impact of the surrounding context or the overlap between words, conveying the same or different senses. A systematic assessment on four scenarios shows that the best monolingual models based on Transformers can adequately disambiguate homonyms in context. However, as they rely heavily on context, these models fail at representing words with different senses when occurring in similar sentences. Experiments are performed in Galician, Portuguese, English, and Spanish, and both the dataset (with more than 3,000 evaluation items) and new models are freely released with this study.

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Probing for idiomaticity in vector space models
Marcos Garcia | Tiago Kramer Vieira | Carolina Scarton | Marco Idiart | Aline Villavicencio
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Contextualised word representation models have been successfully used for capturing different word usages and they may be an attractive alternative for representing idiomaticity in language. In this paper, we propose probing measures to assess if some of the expected linguistic properties of noun compounds, especially those related to idiomatic meanings, and their dependence on context and sensitivity to lexical choice, are readily available in some standard and widely used representations. For that, we constructed the Noun Compound Senses Dataset, which contains noun compounds and their paraphrases, in context neutral and context informative naturalistic sentences, in two languages: English and Portuguese. Results obtained using four types of probing measures with models like ELMo, BERT and some of its variants, indicate that idiomaticity is not yet accurately represented by contextualised models

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Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning
Marcos Garcia
Computational Linguistics, Volume 47, Issue 3 - November 2021

2019

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A Method to Automatically Identify Diachronic Variation in Collocations.
Marcos Garcia | Marcos García Salido
Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change

This paper introduces a novel method to track collocational variations in diachronic corpora that can identify several changes undergone by these phraseological combinations and to propose alternative solutions found in later periods. The strategy consists of extracting syntactically-related candidates of collocations and ranking them using statistical association measures. Then, starting from the first period of the corpus, the system tracks each combination over time, verifying different types of historical variation such as the loss of one or both lemmas, the disappearance of the collocation, or its diachronic frequency trend. Using a distributional semantics strategy, it also proposes other linguistic structures which convey similar meanings to those extinct collocations. A case study on historical corpora of Portuguese and Spanish shows that the system speeds up and facilitates the finding of some diachronic changes and phraseological shifts that are harder to identify without using automated methods.

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Unsupervised Compositional Translation of Multiword Expressions
Pablo Gamallo | Marcos Garcia
Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019)

This article describes a dependency-based strategy that uses compositional distributional semantics and cross-lingual word embeddings to translate multiword expressions (MWEs). Our unsupervised approach performs translation as a process of word contextualization by taking into account lexico-syntactic contexts and selectional preferences. This strategy is suited to translate phraseological combinations and phrases whose constituent words are lexically restricted by each other. Several experiments in adjective-noun and verb-object compounds show that mutual contextualization (co-compositionality) clearly outperforms other compositional methods. The paper also contributes with a new freely available dataset of English-Spanish MWEs used to validate the proposed compositional strategy.

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A comparison of statistical association measures for identifying dependency-based collocations in various languages.
Marcos Garcia | Marcos García Salido | Margarita Alonso-Ramos
Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019)

This paper presents an exploration of different statistical association measures to automatically identify collocations from corpora in English, Portuguese, and Spanish. To evaluate the impact of the association metrics we manually annotated corpora with three different syntactic patterns of collocations (adjective-noun, verb-object and nominal compounds). We took advantage of the PARSEME 1.1 Shared Task corpora by selecting a subset of 155k tokens in the three referred languages, in which we annotated 1,526 collocations with the corresponding Lexical Functions according to the Meaning-Text Theory. Using the resulting gold-standard, we have carried out a comparison between frequency data and several well-known association measures, both symmetric and asymmetric. The results show that the combination of dependency triples with raw frequency information is as powerful as the best association measures in most syntactic patterns and languages. Furthermore, and despite the asymmetric behaviour of collocations, directional approaches perform worse than the symmetric ones in the extraction of these phraseological combinations.

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Pay Attention when you Pay the Bills. A Multilingual Corpus with Dependency-based and Semantic Annotation of Collocations.
Marcos Garcia | Marcos García Salido | Susana Sotelo | Estela Mosqueira | Margarita Alonso-Ramos
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

This paper presents a new multilingual corpus with semantic annotation of collocations in English, Portuguese, and Spanish. The whole resource contains 155k tokens and 1,526 collocations labeled in context. The annotated examples belong to three syntactic relations (adjective-noun, verb-object, and nominal compounds), and represent 58 lexical functions in the Meaning-Text Theory (e.g., Oper, Magn, Bon, etc.). Each collocation was annotated by three linguists and the final resource was revised by a team of experts. The resulting corpus can serve as a basis to evaluate different approaches for collocation identification, which in turn can be useful for different NLP tasks such as natural language understanding or natural language generation.

2018

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A Lexical Tool for Academic Writing in Spanish based on Expert and Novice Corpora
Marcos García Salido | Marcos García | Milka Villayandre-Llamazares | Margarita Alonso-Ramos
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2017

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A Web Interface for Diachronic Semantic Search in Spanish
Pablo Gamallo | Iván Rodríguez-Torres | Marcos Garcia
Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics

This article describes a semantic system which is based on distributional models obtained from a chronologically structured language resource, namely Google Books Syntactic Ngrams.The models were created using dependency-based contexts and a strategy for reducing the vector space, which consists in selecting the more informative and relevant word contexts. The system allowslinguists to analize meaning change of Spanish words in the written language across time.

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Using bilingual word-embeddings for multilingual collocation extraction
Marcos Garcia | Marcos García-Salido | Margarita Alonso-Ramos
Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017)

This paper presents a new strategy for multilingual collocation extraction which takes advantage of parallel corpora to learn bilingual word-embeddings. Monolingual collocation candidates are retrieved using Universal Dependencies, while the distributional models are then applied to search for equivalents of the elements of each collocation in the target languages. The proposed method extracts not only collocation equivalents with direct translation between languages, but also other cases where the collocations in the two languages are not literal translations of each other. Several experiments -evaluating collocations with three syntactic patterns- in English, Spanish, and Portuguese show that our approach can effectively extract large pairs of bilingual equivalents with an average precision of about 90%. Moreover, preliminary results on comparable corpora suggest that the distributional models can be applied for identifying new bilingual collocations in different domains.

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Towards Syntactic Iberian Polarity Classification
David Vilares | Marcos Garcia | Miguel A. Alonso | Carlos Gómez-Rodríguez
Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis

Lexicon-based methods using syntactic rules for polarity classification rely on parsers that are dependent on the language and on treebank guidelines. Thus, rules are also dependent and require adaptation, especially in multilingual scenarios. We tackle this challenge in the context of the Iberian Peninsula, releasing the first symbolic syntax-based Iberian system with rules shared across five official languages: Basque, Catalan, Galician, Portuguese and Spanish. The model is made available.

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A rule-based system for cross-lingual parsing of Romance languages with Universal Dependencies
Marcos Garcia | Pablo Gamallo
Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

This article describes MetaRomance, a rule-based cross-lingual parser for Romance languages submitted to CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. The system is an almost delexicalized parser which does not need training data to analyze Romance languages. It contains linguistically motivated rules based on PoS-tag patterns. The rules included in MetaRomance were developed in about 12 hours by one expert with no prior knowledge in Universal Dependencies, and can be easily extended using a transparent formalism. In this paper we compare the performance of MetaRomance with other supervised systems participating in the competition, paying special attention to the parsing of different treebanks of the same language. We also compare our system with a delexicalized parser for Romance languages, and take advantage of the harmonized annotation of Universal Dependencies to propose a language ranking based on the syntactic distance each variety has from Romance languages.

2016

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Incorporating Lexico-semantic Heuristics into Coreference Resolution Sieves for Named Entity Recognition at Document-level
Marcos Garcia
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper explores the incorporation of lexico-semantic heuristics into a deterministic Coreference Resolution (CR) system for classifying named entities at document-level. The highest precise sieves of a CR tool are enriched with both a set of heuristics for merging named entities labeled with different classes and also with some constraints that avoid the incorrect merging of similar mentions. Several tests show that this strategy improves both NER labeling and CR. The CR tool can be applied in combination with any system for named entity recognition using the CoNLL format, and brings benefits to text analytics tasks such as Information Extraction. Experiments were carried out in Spanish, using three different NER tools.

2014

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Citius: A Naive-Bayes Strategy for Sentiment Analysis on English Tweets
Pablo Gamallo | Marcos Garcia
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)

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Multilingual corpora with coreferential annotation of person entities
Marcos Garcia | Pablo Gamallo
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper presents three corpora with coreferential annotation of person entities for Portuguese, Galician and Spanish. They contain coreference links between several types of pronouns (including elliptical, possessive, indefinite, demonstrative, relative and personal clitic and non-clitic pronouns) and nominal phrases (including proper nouns). Some statistics have been computed, showing distributional aspects of coreference both in journalistic and in encyclopedic texts. Furthermore, the paper shows the importance of coreference resolution for a task such as Information Extraction, by evaluating the output of an Open Information Extraction system on the annotated corpora. The corpora are freely distributed in two formats: (i) the SemEval-2010 and (ii) the brat rapid annotation tool, so they can be enlarged and improved collaboratively.

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An Entity-Centric Coreference Resolution System for Person Entities with Rich Linguistic Information
Marcos Garcia | Pablo Gamallo
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

2012

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Dependency-Based Open Information Extraction
Pablo Gamallo | Marcos Garcia | Santiago Fernández-Lanza
Proceedings of the Joint Workshop on Unsupervised and Semi-Supervised Learning in NLP

2011

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Evaluating Various Linguistic Features on Semantic Relation Extraction
Marcos Garcia | Pablo Gamallo
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011

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Dependency-Based Text Compression for Semantic Relation Extraction
Marcos Garcia | Pablo Gamallo
Proceedings of the RANLP 2011 Workshop on Information Extraction and Knowledge Acquisition